Sammenlign metoder

	Risikojusteret overlevelsesanalyse	Cox Proportional Hazards
Fagområde	Epidemiologi	Epidemiologi
Familie	Process / pipeline	Process / pipeline
Oprindelsesår	1972 (Cox regression); broader covariate-adjusted survival methods developed 1970s–1990s	1972
Ophavsperson	D. R. Cox (regression framework); extensions via Kaplan & Meier, Breslow, and others	Sir David Roxbee Cox
Type	Observational and experimental analytical method	Semi-parametric regression model
Oprindelig kilde	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society, Series B, 34(2), 187–220.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Aliasser	covariate-adjusted survival analysis, adjusted time-to-event analysis, risk-stratified survival analysis, adjusted Kaplan-Meier / Cox analysis	Cox regression, Cox PH model, proportional hazards model, CPH
Relaterede	5	5
Resumé	Risk-adjusted survival analysis estimates the time to an event of interest — such as death, relapse, or hospital readmission — while simultaneously accounting for baseline differences in patient characteristics (covariates). By incorporating confounders such as age, comorbidities, or disease severity, it produces hazard ratios, survival curves, and median survival estimates that are attributable to the factor of interest rather than to pre-existing risk differences between groups.	The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research.